The Developers' Guide to Python 3 Programming

Want to Code? Python 3 is the Perfect Place to Start

Python is an excellent first programming language because of its simple syntax, coding principles, and easy readability. It is a simple, yet powerful programming language that allows developers to build complex websites without complex code. First time coders will find Python to be a great jumping off point, and can use the skills they learn in this course to take on greater coding challenges.

Eduonix creates and distributes high-quality technology training content. Their team of industry professionals has been training manpower for more than a decade. They aim to teach technology the way it is used in the industry and professional world. They have a professional team of trainers for technologies ranging from Mobility, Web and Enterprise, and Database and Server Administration.

If you have any questions, feel free to contact Eduonix at info@eduonix.com.

Step by Step: Build a Data Analysis Program

Learn How to Process, Analyze, & Visualize Data Using Python

The world is more data-driven than ever, and Python offers solutions for handling, analyzing, and visualizing large amounts of data effectively. Through this course, you'll learn the valuable data analysis functions of Python that can help separate you from your peers, and make a positive impact in your career.

Ardit Sulce received his master's degree in Geospatial Technologies from the Institute of Geoinformatics at University of Muenster, Germany. He also holds a Bachelor's degree in Geodetic Engineering.

Ardit offers his expertise in Python development on Upwork where he has worked with companies such as the Swiss in-Terra, Center for Conservation Geography, and Rapid Intelligence. He is the founder of PythonHow where he authors written tutorials about the Python programming language.

Details & Requirements

Length of time users can access this course: lifetime

Access options: web streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: all levels

Compatibility

Internet required

Course Outline

Getting Started

Course Introduction (4:21)

An Example of Using Python for Data Analysis And Visualization (8:03)

Installing Python and Python Libraries (7:54)

Python Editors: Spyder and iPython (3:21)

Installing Python and its Libraries (8:24)

Python Basics

Section Intro

Variables (2:47)

Strings and Numbers (4:25)

If, Else, and Indentation (4:06)

Functions (3:09)

Sequences (2:57)

Collections (3:28)

Working with Sequences (7:27)

Iterating (3:37)

Working with Files

Working with Files (5:29)

Handling Files Easily (1:44)

Working with Directories (3:50)

Working with File Paths - Advanced (6:47)

Iterating Through Files (6:09)

Downloading Files from FTP Sites

Section Intro (1:34)

Navigating Through FTP Directory Trees with Python (7:00)

Storing Python Code (4:32)

Creating an FTP Function (2:29)

Downloading an FTP File (8:32)

Practice No.1: Creating an FTP File Downloader (13:42)

Working with Archive Files

Extracting ZIP, TAR, GZ and Other Archive Formats (3:41)

Extracting RAR Files (1:57)

Practice No.2: Creating a Batch Archive Extractor (5:52)

Working with TXT and CSV Files

Section Intro (1:22)

Reading Delimited TXT and CSV Files (10:06)

Exporting Data from Python to Files (4:14)

Reading Fixed Width Files (1:58)

Exporting Data Back to HTML and Other File Formats (1:02)

Exercise 1 of 6

Solution 1 of 6

Getting Started with Pandas - a Powerful Data Analysis Library

Get Started with Pandas (6:16)

Practice No.3: Calculating and Adding Columns to CSV Files (4:57)

Exercise 2 of 6

Solution 2 of 6

Concatenating and Joining Tables of Dat a with Pandas

Practical No.4: Concatenating Multiple CSV files (6:18)

Exercise 3 of 6

Solution 3 of 6

Practice No. 5: Joining Data Based on a Matching Column (8:59)

Exercise 4 of 6

Solution 4 of 6

Exercise 5 of 6

Solution 5 of 6

Data Aggregation

Practice No. 6: Pivoting Large Amounts of Data (7:41)

Visualizing Data

Data Visualization with Python (11:31)

More Visualization Techniques (12:23)

Practice No. 7: Producing JPG Files (3:08)

Exercise 6 of 6

Solution 6 of 6

Mapping Spatial Data

Programmatically Creating KML Google Earth Files with Python (4:37)

Practice No. 8: Creating KML Google Earth Files from CSV Data (7:46)

Putting Everything Together

User Interaction (6:07)

Practice No. 9: Polishing the Program I (5:00)

Practice No, 10: Polishing the Program II (5:30)

Practice No. 11: Creating Python Modules (5:00)

Bonus Section: Using Python in Jupyter Notebooks to Boost Productivity

The Python Mega Course: Build 10 Real World Applications

Explore the Power of Python By Actually Building Apps With Python

The best way to learn Python is by using Python, and this massive course will teach you while you develop real life applications. Over the course, you'll truly begin to appreciate the many, many uses of Python as you build web applications, database applications, web visualizations, and much more. By course's end, you will have built 10 applications that you can be proud of, and have the tools to go off on your own into the world of Python programming.

Ardit Sulce received his master's degree in Geospatial Technologies from the Institute of Geoinformatics at University of Muenster, Germany. He also holds a Bachelor's degree in Geodetic Engineering.
Ardit offers his expertise in Python development on Upwork where he has worked with companies such as the Swiss in-Terra, Center for Conservation Geography, and Rapid Intelligence. He is the founder of PythonHow where he authors written tutorials about the Python programming language.

Important Details

Length of time users can access this course: lifetime

Access options: web streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: all levels

Requirements

Internet required

Course Outline

Getting Started

Course Introduction (4:14)

Tips for Learning Efficiency (3:04)

The Companion Cheatsheet (1:04)

Three Typical Python Programs

Installing Python

Creating a Basic Python program

Python Components

Variables and Functions

Variables

Functions

Using the Python Interactive Shell

Setting up and Working with the Atom Editor

Data Types

Numbers

More on Numbers: Using Python as a Calculator

Strings

Lists and Tuples

Dictionaries

Summary of Datatypes

Conditionals

Conditional Blocks

In-line Conditionals

Loops and User Input

Loops

For Loops

User Input

While Loop

For Loop with Multiple Lists

File Handling

Introduction to File Handling

Opening and Reading a File

Opening and Writing Text to a Text Fle

Appending to a Text File

The Rest of File Handling Methods

The "With" Statement

More Functionalities

Introduction

Modules, Libraries, and Packages

Commenting and Documenting your Code

Lecture 3 Dates and times

Application 1: Building a Text Generator

Demonstration of the Text Generator Application

Building Version 1

Building Version 2

Building Version 3

Data Analysis with Pandas

What is Pandas

Getting Started with Pandas

Getting Started with Jupyter Notebooks

Loading Data in Python fro CSV, TXT, Excel and JSON Files

Indexing and Slicing Dataframes

Dropping Dataframe Columns and Rows

Updating and Adding New Columns and Rows

Example: Geocoding Addresses with Pandas and Geopy

Numpy

What is Numpy

Creating Numpy Arrays from Images and Vice-Versa

Indexing, Slicing and Iterating

Stacking and Splitting

Application 2: Creating Leaflet Webmaps with Python and Folium

Demonstration of the Web Mapping Application

Creating an Open Street Map with Python

Adding Markers to the Map

Adding Markers to the Map from CSV Data

Rule-based Coloring of Markers

More on Rule-based Styling

Calculating the Map Center from the Input Data

Adjusting the Code for the Latest Version of Folium

Adding a Choropleth Map from GeoJson

Adding a Layer Control Panel

Application 3: Building a Website Blocker

Demonstration of the Website Blocker Application

Application Architecture

Setting up the Script

Setting up the Infinite Loop

Implementing the First Part

Implementing the Second Part

Scheduling the Python Program on Windows

Scheduling the Python Program on Mac and Linux

Application 4: Building a Website with Python and Flask

Demonstration of the Website

Building Your First Website

Returning HTML Templates

Adding a Navigation Menu

Adding CSS Styling

Creating a Python Virtual Environment

Deploying the Website to a Live Server

Maintaining the Website

Building Graphical User Interfaces with Tkinter

Introduction to Tkinter

Setting up a GUI with Widgets

Connecting GUI Widgets with Callback Functions

Python for Interacting with SQLite and PostgreSQL Databases

Introduction to Working with Databases

Connecting and Inserting Data to SQLite via Python

Selecting, Inserting, Deleting, and Updating SQLite Records

Introduction to PostgreSQL Psycopg2

Selecting, Inserting, Deleting, and Updating PostgreSQL Records

Application 5: Building a Desktop Database Application

Demonstration of the Database Application

User Interface Design

Building the Front-end Interface

Building the Back-end

Connecting the Front-end to the Back-end, Part 1

Connecting the Front-end to the Back-end, Part 2

Creating a Standalone Executable Version of the Program

Object Oriented Programming

Object Oriented Programming Explained

Turning this Application into OOP Style, Part 1

Turning this Application into OOP Style, Part 2

Creating a Bank Account Object

Inheritance

OOP Glossary

Python for Image and Video Processing with OpenCV

Introduction

Installing OpenCV for Python

Loading, Displaying, Resizing, and Writing Images with Python

Face Detection

Capturing Video

Application 6: Building a Webcam Motion Detector

Demonstration of the Motion Detector Application

Detecting Objects from the Webcam

Recording Motion Time

Python for Interactive Data Visualization on the Browser

Introduction to Bokeh

The Bokeh Charts Interface

The Bokeh Plotting Interface

Customizing Pot Styles

Understanding the Structure Behind the Graphs

Time-series Plots

More Visualization Examples with Bokeh

Plotting Time Intervals of the Motion Detector

Hover Tool Implementation

Webscraping

Section Introduction

The Concept Behind Webscraping

Scraping a Webpage with Requests and BeautifulSoup

Application 7: Scraping Real Estate Property Data

Demonstration of the Webscraping Application

Understanding the Problem and Loading the Webpage in Python

Extracting Divisions of All Properties

Extracting Addresses and Property Details

Extracting Elements with no Unique Identifiers

Saving the Extracted Data in CSV Files

Crawling Through Webpages

Application 8: Building a Web-based Financial Graph

Demonstration of the Financial Analysis Application

Downloading Various Datasets with Python

Understanding Stock Market Data

Understanding Stock Market Data Candlestick Charts

Building Chart Candlesticks with Bokeh Quadrants

Building Chart Candlesticks with Bokeh Rectangles

Building Candlestick Segments

Stylizing the Chart

The Concept Behind Embedding a Bokeh Chart in a Webpage

Embedding the Bokeh Chart in a Webpage

Deploying the Chart Website to a Live Server

Application 9: Building a Data Collector Web App

Demonstration of the Web Application

Steps for Building a PostgreSQL Database-enabled Web Application

Building the Front-end: HTML Part

Building the Front-end: CSS Part

Building the Back-end: Getting User Input

Building the Back End: Creating the PostGreSQL Database Model

Building the Back End: Storing User Data to the Database

Building the Back End: Emailing Database Values Back to the User

Building the Back End: Sending Statistics to Users

Deploying the Web Application to a Live Server

Bonus Lecture: User Downloads and Uploads

Application 10: Student Project on Building a Geocoder Web Service

Demonstration of the Geocoding Web Service Application and Project Requirements

The Complete Computer Vision Course with Python

Contribute to the Next Generation of Consumer & Enterprise Applications

Have you ever wondered how things like self-driving cars, Google image searches, Snapchat and Instagram filters are created? While there are many answers to this question, the umbrella answer is computer vision. In this course, you'll use Python to build a variety of tools that reflect the broad range of computer vision techniques. These technologies are powering the next generation of consumer and enterprise applications and the time to jump in the game is now!

Access 43 lectures & 7 hours of content 24/7

Build a receipt segmenter to find text in an image

Count coins & dollar bills in an image after creating a currency counter

Find Legend of Zelda rupees using a pattern matching algorithm

Design a face swapping app

Discuss the mathematical theory & processes behind computer vision

Understand fundamental computer vision & image processing techniques

Pablo Farias Navarro is a software developer and founder of ZENVA. Since 2012, Pablo has been teaching online how to create games, apps and websites to over 150,000 students through the Udemy and Zenva Academy platforms, and created content for companies such as Amazon and Intel. Pablo is a member of the Intel Innovator Program in the Asia Pacific, and has run live programming workshops in San Francisco, Brisbane and Bangalore. Pablo holds a Master in Information Technology (Management) degree from the University of Queensland (Australia) and a Master of Science in Engineering degree from the Catholic University of Chile.

Learn Python 3 from Scratch

Build System Securities & Connect Your Hardware Using Python

Python is a great programming language to learn in conjunction with your new Wio Link, as you can also connect to the Rest API to communicate with your board in Python. Overall demand for Python programming has exploded in recent years as many industries are rapidly transitioning to Python and building automation tools. This comprehensive course will introduce you to the basics of Python 3, the newest series of this powerful coding language. Give yourself a leg up over other developers by adding Python to your programming repertoire.

Python Tutorial: Python Network Programming - Build 7 Apps

Learn to Write Powerful Code by Building Apps from Scratch

Over 10000 satisfied students have enrolled in this highly-rated Python courses across the Web. Why? Because this course will teach you essential Python concepts that are extremely relevant in any tech career, not to mention perfect for building amazing network tools. Follow along with the below hands-on projects, and you'll solidify the concepts and skills you need to confidently code with Python.

Mihai Catalin Teodosiu holds a degree in Telecommunications and Information Technology from University Politehnica of Bucharest, Romania, as well as the CCNP, CCNA, CCDA, JNCIA, and ISTQB CTFL certifications. He has been working as a Network Quality Assurance Engineer since 2010, testing the OS for Nortel/Avaya L3 switches.

5+ years experience in the Networking and Testing/Quality Assurance industries.

Python Web Programming

Start Programming the Right Way by Diving Into Python

Python is considered by many experts to be the ideal learning language for first time programmers because it is syntactically fairly straight-forward and has an enormous reach of applications. It's an excellent stepping stone for other, more complex languages, yet Python programmers are also in constant demand. This course dives into all aspects of web programming with Python, and will be the perfect first step for your coding odyssey.

Access 58 lectures & 6 hours of content 24/7

Acquire an in-depth understanding of Python web programming

Get hands on experience working w/ Python files & building programs

Access & parse the web w/ Python

Manage a database & a remote server

Create a basic website w/ Python

Run code via a Virtual Private Server

At Stone River eLearning, technology is all we teach. If you're interested in programming, development or design - we have it covered.

Check out our huge catalog of courses and join the over 300,000 students currently taking Stone River eLearning courses. We currently offer 125+ different technology training courses on our Stone River eLearning website and are adding new courses on hot and trending topics every month. A subscription option is available for those with a real passion for learning.

Taming Big Data with Apache Spark and Python

Learn the Techniques Used by Major Companies to Manage Mass Data Sets

Have you ever wondered how major companies and organizations manage all of the massive amounts of data they collect? The answer is Big Data technology, and Big Data engineers are in big-time demand. Major employers like Amazon, eBay, and NASA JPL use Apache Spark to extract data sets across a fault-tolerant Hadoop cluster. Sound complicated? That's why you should take this course, to learn these techniques and more, using your own system at home.

Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

Details & Requirements

Length of time users can access this course: lifetime

Access options: web streaming

Certification of completion not included

Redemption deadline: redeem your code within 30 days of purchase

Experience level required: all levels

Compatibility

Internet required

Course Outline

Getting Started with Spark

Introduction

[Activity] Installing Enthought Canopy

[Activity] Installing a JDK

[Activity] Installing Spark

[Activity] Installing the MovieLens Movie Rating Dataset (3:35)

[Activity] Run your first Spark program! Ratings histogram example.

Spark Basics and Simple Examples

Introduction to Spark

The Resilient Distributed Dataset (RDD)

Ratings Histogram Walkthrough

Key/Value RDD's, and the Average Friends by Age Example

[Activity] Running the Average Friends by Age Example

Filtering RDD's, and the Minimum Temperature by Location Example

[Activity]Running the Minimum Temperature Example, and Modifying it for Maximums

[Activity] Running the Maximum Temperature by Location Example

[Activity] Counting Word Occurrences using flatmap()

[Activity] Improving the Word Count Script with Regular Expressions

[Activity] Sorting the Word Count Results (7:44)

[Exercise] Find the Total Amount Spent by Customer (4:01)

[Excercise] Check your Results, and Now Sort them by Total Amount Spent. (5:08)